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Extracting Cycle-aware Feature Curve Networks from 3D Models

文献类型：期刊论文

作者Lu, Zhengda1,2; Guo, Jianwei1,2; Xiao, Jun2; Wang, Ying2; Zhang, Xiaopeng1,2; Yan, Dong-Ming1,2
刊名COMPUTER-AIDED DESIGN
出版日期2021-02-01
卷号131页码:11
关键词Shape analysis Feature curve network Segmentation
ISSN号0010-4485
DOI10.1016/j.cad.2020.102949
通讯作者Guo, Jianwei(jianwei.guo@nlpr.ia.ac.cn) ; Xiao, Jun(xiaojun@ucas.ac.cn)
英文摘要Meaningful feature curves provide high-level shape representation of the geometrical shapes and are useful in various applications. In this paper, we propose an automatic method on the basis of the quadric surface fitting technique to extract complete feature curve networks (FCNs) from 3D surface meshes, as well as finding cycles and generating a high-quality segmentation. In the initial collection of noisy and fragmented feature curves, we first fit the quadric surfaces of each curve and the corresponding neighbor vertices to filter out non-salient or noisy feature curves. Then we conduct a feature extension step to address the curve intersections and form a closed FCN. Finally, we regard circle curves as cycles in the complete FCN and segment the mesh into patches to reveal a highly structured representation of the input geometry. Experimental results demonstrate that our algorithm is more robust for FCN extraction from complex input meshes and achieves higher quality patch layouts compared with the state-of-the-art approaches. We also verify the validity of extracted feature curve cycles by applying them to surface reconstruction. (c) 2020 Elsevier Ltd. All rights reserved.
资助项目National Key R&D Program, China[2018YFB2100602] ; NSFC, China[61802406] ; NSFC, China[61772523] ; Beijing science and technology project, China[Z181100003818019] ; Youth Innovation Promotion Association of CAS, China[Y201935] ; Beijing Natural Science Foundation, China[L182059] ; Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems Beihang University, China[VRLAB2019B02] ; CCF-Tencent Open Research Fund, China[RAGR20190105] ; Key Research Program of Frontier Sciences CAS, China[QYZDY-SSW-SYS004]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000596601700004
出版者ELSEVIER SCI LTD
资助机构National Key R&D Program, China ; NSFC, China ; Beijing science and technology project, China ; Youth Innovation Promotion Association of CAS, China ; Beijing Natural Science Foundation, China ; Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems Beihang University, China ; CCF-Tencent Open Research Fund, China ; Key Research Program of Frontier Sciences CAS, China
源URL[http://ir.ia.ac.cn/handle/173211/42814]  
专题模式识别国家重点实验室_三维可视计算
通讯作者Guo, Jianwei; Xiao, Jun
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Zhengda,Guo, Jianwei,Xiao, Jun,et al. Extracting Cycle-aware Feature Curve Networks from 3D Models[J]. COMPUTER-AIDED DESIGN,2021,131:11.
APA Lu, Zhengda,Guo, Jianwei,Xiao, Jun,Wang, Ying,Zhang, Xiaopeng,&Yan, Dong-Ming.(2021).Extracting Cycle-aware Feature Curve Networks from 3D Models.COMPUTER-AIDED DESIGN,131,11.
MLA Lu, Zhengda,et al."Extracting Cycle-aware Feature Curve Networks from 3D Models".COMPUTER-AIDED DESIGN 131(2021):11.

入库方式： OAI收割

来源：自动化研究所

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